ArticleACS photonics2026
Seeing Beyond RGB Capabilities: Data-Driven and Physics-Guided Broadband Spectral Extrapolation of Plasmonic Nanostructures by Deep Learning.
Article in ACS photonics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Localized surface plasmons confine light within deep-subwavelength volumes, enabling ultrasensitive near-field responses that underpin a wide spectrum of interdisciplinary technologies. Yet this extreme localization also amplifies unwanted "noise" from local nanomorphological variations, resulting in spectral complexities and inconsistencies that have long hindered reproducible and scalable nanophotonics. In this context, optical identification and screening of nanostructures with consistent, target responses offers a practical strategy. However, conventional imaging and spectroscopies, including hyperspectral methods, are limited by a resolution-throughput trade-off, motivating the development of faster, high-precision approaches. Here, we introduce
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